1. Field of the Invention
This invention relates to information handling.
2. Description of the Prior Art
The problem of identifying and retrieving media content items such as audio and/or video items from asset management systems is a longstanding one. Often digital audio/video files have no associated textual metadata and even the filename may simply be an identification code which is meaningless to a human user.
Systems have been proposed which attempt to allow a user to search a content repository by identifying video and/or audio statistics of an item of interest and search in the repository for similar content items. Such statistics are often called “ground truth” metadata, as they are derived in a repeatable way from video and audio properties of the content. The searching may be performed by defining a feature vector (based on at least a set of significant aspects of the ground truth metadata) for each available content item, and detecting close matches by distance in the vector space. This type of search may return a subset of information from which the user can subjectively determine which are relevant to his requirements. It has been proposed that a user may select relevant hits subjectively, and cross search their feature vectors back into the repository to find further similar content items or hits. This will be termed a “reinforced find similar” search.
Some asset management repositories may include content items having associated textual metadata, while other items in the same repository have no associated metadata. New content items may be ingested with or without associated textual metadata. A search by ground truth metadata can be used to generate a visual representation of available content items to give the user an appreciation of what the types of content stored in the repository. The user may select a number of candidate items from this visualisation and perform a keyword search on those selected to find content items required. Clearly, those items without textual metadata can only be identified as relevant from the visualisation search. It has been proposed that when ingesting new content items into the repository without having associated textual metadata, a feature vector for the new content item could be derived and searched into the asset management system to identify similar content items. For example, the closest match in vector space to the new item could be identified and, if it has associated textual metadata, that metadata could be automatically assigned to the new content item. Thus the new content item can be identified by a textual metadata search without the burdensome requirement for a human to review it and assign, manually metadata to it.
Of course, this has some disadvantages, as often, the metadata assigned to a new content item will not be totally accurate. For example the repository may include a number of shots of racing cars on a track and each car has a metadata defining it as a Formula One racing car (A). There may also be a number of shots of motorcycles parked by the edge of a street with metadata defining the shot as a motorcycle (B). If a new shot is ingested of a superbike race on a racing track (C), then an automated system may determine that (A) is relatively more similar to (C) than (B) due to the presence of a racing track. In such cases, (C) would be incorrectly assigned the metadata “Formula One Racing Car” rather than “motorcycle”. The risk of this happening could be reduced by ensuring that metadata is only assigned when a similar item is identified within a threshold distance in the vector space. Alternatively, the system could identify say, the 20 closest items and process their metadata to identify a term frequency for individual words or phrases and assign e.g. the top three words/phrases to the newly ingested content item.
Irrespective, this would be a fairly risky strategy for database administration and could result in many incorrectly labelled items. Further if those incorrectly labelled items were themselves used to automatically populate newly ingested items incorrectly, the result would be a database which was not fit for purpose.
It is an object of the present invention to mitigate or alleviate the above problem.